Spectral Efficiency of Random Time-Hopping CDMA

Traditionally paired with impulsive communications, Time-Hopping CDMA (TH-CDMA) is a multiple access technique that separates users in time by coding their transmissions into pulses occupying a subset of $N_\mathsf{s}$ chips out of the total $N$ included in a symbol period, in contrast with traditional Direct-Sequence CDMA (DS-CDMA) where $N_\mathsf{s}=N$. This work analyzes TH-CDMA with random spreading, by determining whether peculiar theoretical limits are identifiable, with both optimal and sub-optimal receiver structures, in particular in the archetypal case of sparse spreading, that is, $N_\mathsf{s}=1$. Results indicate that TH-CDMA has a fundamentally different behavior than DS-CDMA, where the crucial role played by energy concentration, typical of time-hopping, directly relates with its intrinsic "uneven" use of degrees of freedom.Comment: 26 pages, 13 figure

Local spillovers, production technology and the choice to make and/or buy. Empirical evidence from Emilia Romagna

By exploiting a new rich firm-level dataset, this paper investigates the decision to subcontract production activities (outsourcing) with respect to vertically integrate them. In particular, we aim at identifying the main factors underlying the decision to either fully or partially decentralise production activities by mechanical firms located in Emilia Romagna (Italy). In so doing, we first account for firm characteristics, such as size, age and the skill composition of the labour force, then we focus on labour costs per employee, product diversity and the presence of the firm on international markets. Finally, and differently from previous research, we include in the analysis both the qualitative composition of the production process, as given by the stages of production potentially developed by the firm, and the industrial composition of the local market. On this last purpose, we estimate the relationship between the propensity and the intensity of concurrent and total sourcing and the main sources of agglomeration economies identified in the literature: specialisation economies, variety and urbanisation economies. Our estimates show a particularly strong and positive relation between the intensity of 'pure' outsourcing and our measure of variety, workforce skill intensity and the internal composition of production, while a negative relation emerges with respect to firm size, age and labour cost. Results concerning concurrent sourcing, instead, appear weaker, but, differently from the case of full outsourcing, we nd a positive relationship with rm size and product diversity.

Time series kernel similarities for predicting Paroxysmal Atrial Fibrillation from ECGs

We tackle the problem of classifying Electrocardiography (ECG) signals with the aim of predicting the onset of Paroxysmal Atrial Fibrillation (PAF). Atrial fibrillation is the most common type of arrhythmia, but in many cases PAF episodes are asymptomatic. Therefore, in order to help diagnosing PAF, it is important to design procedures for detecting and, more importantly, predicting PAF episodes. We propose a method for predicting PAF events whose first step consists of a feature extraction procedure that represents each ECG as a multi-variate time series. Successively, we design a classification framework based on kernel similarities for multi-variate time series, capable of handling missing data. We consider different approaches to perform classification in the original space of the multi-variate time series and in an embedding space, defined by the kernel similarity measure. We achieve a classification accuracy comparable with state of the art methods, with the additional advantage of detecting the PAF onset up to 15 minutes in advance

Effects of material and non-material rewards on remembering to do things for others.

Recent research has shown that pro-social prospective memory, i.e., remembering to do something for others, is negatively affected by the presence of small material rewards. While this competition between pro-social and self-gain motives leads to poor memory for the intention, people do not seem to be aware of the possible collision effects of competing motives (Brandimonte et al., 2010). Extending research on this general topic, in two activity-based prospective memory (PM) experiments, we explored the effects of different types and amount of rewards on pro-social prospective remembering. In Experiment 1, participants could receive no reward, a low material reward (1 euro), or a high material reward (20 euro) for their pro-social PM action. In Experiment 2, their pro-social PM performance could be rewarded or not with an image reward (disclosure of their altruistic behavior). Results revealed that introducing a small material reward (Experiment 1) or a non-material reward (Experiment 2) impaired pro-social PM. However, introducing a high material reward eliminated the impairment (Experiment 1). Importantly, in Experiment 1, ongoing task performance in the pro-social condition was faster than in the No PM condition. However, in Experiment 2, ongoing task costs emerged in the presence of a non-material reward, as compared to the pro-social condition. Also, results from two independent ratings showed that people's predictions on their future pro-social actions were at odds (Experiment 1) or in line (Experiment 2) with actual PM performance. It is suggested that, according to the nature and amount of rewards, memory for a pro-social future action may be modulated by conscious or unconscious motivational mechanisms

Chapter Media and fake news: An analysis of citizens’ attitudes toward misinformation in European countries

The rapid changes determined by the rise of Internet and the recent development of social media in daily life have led to profound consequences on the quantity and quality of data made available and on the mechanisms of their dissemination. The rapid spread of on-line disinformation is one of the most discussed topic, and has been identified as one of the top-trends in modern societies by the World Economic Forum, also because of the link between these processes and political communication. Thanks to the availability of micro-data from the Flash Eurobarometer survey on “Fake news and disinformation online”, the present work aims at analyzing the attitude of European citizens toward fake news and disinformation. In a first step, cluster of citizens are identified according to their level of trust in media news, in relation to different types of media. Given the categorical nature of the variables considered, k-mode clustering is implemented. Secondly, the main determinants of news trust levels are analyzed, through regression models for categorical response variables. Preliminary results show that socio-demographic characteristics as well as technological use have an influence on trust in the media, which in turn determines different approaches on the role of institutions in tackling disinformation. The relevance of fake news in contemporary period and its potential consequences on the political side require a reflection on the role of statistical literacy and of official statistical institutes in dealing with disinformation in the post-truth era

Fundamental Limits of Low-Density Spreading NOMA with Fading

Spectral efficiency of low-density spreading non-orthogonal multiple access channels in the presence of fading is derived for linear detection with independent decoding as well as optimum decoding. The large system limit, where both the number of users and number of signal dimensions grow with fixed ratio, called load, is considered. In the case of optimum decoding, it is found that low-density spreading underperforms dense spreading for all loads. Conversely, linear detection is characterized by different behaviors in the underloaded vs. overloaded regimes. In particular, it is shown that spectral efficiency changes smoothly as load increases. However, in the overloaded regime, the spectral efficiency of low- density spreading is higher than that of dense spreading

Comparing alternative distributional assumptions in mixed models used for small area estimation of income parameter

Linear Mixed Models used in small area estimation usually rely on normality for the estimation of the variance components and the Mean Square Error of predictions. Nevertheless, normality is often inadequate when the target variable is income. For this reason, in this paper we consider Linear Mixed Models for the log-transformed income (which require back-transformation for prediction of means and totals on the variable’s original scale) and a Generalized Linear Mixed Model based on the Gamma distribution. Various prediction methods are compared by means of a simulation study based on the ECHP data. Standard predictors obtained from Linear Mixed Model for the untrasformed income are shown to be preferable to the considered alternatives, confirming their robustness with respect to the failure of the normality assumption